Women in Data®

About the Company

Women are hugely under-represented in the Data industry – as things stand, male Analysts and Data Scientists outnumber their female colleagues 4 to 1.

Addressing this imbalance isn’t just the right thing to do ethically. Data shows that everything from workplace satisfaction, to business profitability significantly improve when an organisation strives for greater diversity and inclusivity.

Women in Data® plays a key role in driving for more accurate representation wherever data is being gathered and analysed. We provide the platform that allows professionals at all levels to share their knowledge and experience, while working alongside businesses to help them embrace and develop the enormous advantages generated by diversity.

The changes we’re affecting are cultural and systemic.

Offering everything from professional networking and knowledge transfer, to our Women’s Health Commission, Women’s Safety Commission, MenopauseX and Girls in Data initiative.

Our work is creating measurable impact for the partners we support and the community we host.

Listed Jobs

Company Name

Women in Data®

Job Title

Data & AI Strategy Analyst

Job Description

Job title: Data & AI Strategy Analyst Role Summary: Lead the development, execution, and monitoring of a data and AI strategy that aligns with business objectives across commercial, retail, and health insurance units, driving AI adoption, governance, and culture change. Expectations: - Deliver a forward‑looking data and AI roadmap that reflects industry trends and supports business growth. - Influence senior stakeholders to secure commitment to AI initiatives and embed data‑driven decision making. Key Responsibilities: 1. Design and implement a multi‑unit AI strategy, ensuring consistency with corporate goals and regulatory requirements. 2. Identify, prioritize, and manage a pipeline of high‑impact AI use cases by collaborating with business leaders. 3. Partner with technology and data teams to shape platform evolution, governance frameworks, and data architecture that enable AI delivery. 4. Translate emerging technologies and market disruptions into actionable strategic opportunities. 5. Advise on organisational change, championing data literacy and a culture that embraces AI across all functions. 6. Monitor strategy execution, measuring outcomes and iterating based on performance insights. Required Skills: - Strategic thinking and experience delivering data/AI programmes, preferably in insurance or analytics. - Strong influencing and stakeholder‑management skills with a record of building consensus across technical and business groups. - Analytical mindset capable of assessing complex business needs, evaluating solutions, and defining measurable KPIs. - Deep knowledge of data platforms, governance, business processes, and their role in scaling AI. - Change‑management experience, guiding organisations through digital transformation and adoption. - Proactive problem‑solving attitude and passion for driving AI‑enabled change. Required Education & Certifications: - Bachelor’s degree in Business, Data Analytics, Computer Science, or related discipline (or equivalent experience). - Professional certifications in data or AI (e.g., Certified Analytics Professional, AI strategy credentials) are advantageous. (Eligibility to work in the UK and willingness to travel are required.)

Redhill, United kingdom

Hybrid

24-11-2025

Company Name

Women in Data®

Job Title

Senior Data Scientist – Gen AI – 12 month FTC

Job Description

**Job Title** Senior Data Scientist – Generative AI (12‑month Fixed Term Contract) **Role Summary** Lead the development of end‑to‑end generative AI solutions that enhance decision‑making, customer experience, and competitive advantage across the organization. Partner with business stakeholders to translate research into production‑ready products such as chatbots, document summarization, and image generation. **Expectations** - Deploy AI models that meet business requirements and deliver measurable impact. - Communicate complex technical concepts clearly to non‑technical stakeholders. - Ensure data quality, documentation, and peer‑reviewed deliverables. - Maintain continuous learning of cutting‑edge research and translate findings to practical solutions. **Key Responsibilities** - Collect and engineer high‑volume, high‑quality datasets for generative AI projects. - Perform exploratory data analysis to inform model design and feature engineering. - Develop, validate, and productionize machine‑learning pipelines in Python, SQL, and supporting tools. - Visualize model outcomes and analytical results using best practices. - Automate analytics and maintain code quality through unit tests and documentation. - Liaise with data, engineering, and business teams to align solutions with strategic objectives. - Review and implement relevant research papers to extend capabilities. - Conduct peer reviews to guarantee accuracy and consistency of deliverables. **Required Skills** - Advanced knowledge of machine learning and generative AI techniques (e.g., transformers, diffusion models). - Proficiency in Python (scikit‑learn, PyTorch, TensorFlow, Hugging Face) and SQL for data manipulation. - Experience transforming raw data into ready‑to‑use datasets for AI. - Ability to automate analysis and build reproducible model pipelines. - Strong stakeholder‑management and communication skills. - Demonstrated ability to document and audit workflows. **Required Education & Certifications** - Bachelor’s or Master’s degree in a quantitative discipline (Statistics, Computer Science, Data Science) or equivalent professional experience. - Relevant certifications (e.g., TensorFlow, AWS Machine Learning, Microsoft Certified: Azure AI Engineer) are a plus but not mandatory.

London, United kingdom

Hybrid

Senior

09-12-2025

Company Name

Women in Data®

Job Title

Associate Data Scientist

Job Description

**Job Title:** Associate Data Scientist **Role Summary:** Develop and deploy in‑house data science solutions that automate decision‑making and deliver actionable insights across the business. Work within cross‑functional agile squads to design, build, and maintain models and analytical products, ensuring high quality and effective communication of results to stakeholders. **Expectations:** - Deliver production‑ready machine‑learning models and analyses in a corporate environment. - Collaborate with engineers, product managers, and data engineers to translate business requirements into data‑driven solutions. - Present complex technical findings clearly to non‑technical audiences and influence decision‑making. - Take initiative and work independently while adhering to software engineering best practices. **Key Responsibilities:** - Design, implement, and validate predictive models (tree‑based, linear regression, etc.) using Python, SQL, and Scikit‑Learn. - Build data pipelines and perform feature engineering on clean, well‑documented datasets. - Deploy models to a production environment, manage model monitoring, and maintain performance metrics. - Conduct hypothesis testing, experimental design, and causal inference studies to support business decisions. - Participate in code reviews, pair programming, and knowledge‑sharing sessions to uphold code quality and continuous learning. - Collaborate with supply‑chain and retail teams on projects such as demand forecasting, price elasticity, and optimised product substitution. **Required Skills:** - Python (pandas, NumPy, sklearn, etc.) and SQL proficiency. - Strong statistical foundation: regression, hypothesis testing, experimental design. - Experience with tree‑based models and model deployment. - Familiarity with software engineering practices, Git, and code review processes. - Excellent presentation and business communication skills. - Ability to work independently, set goals, and deliver results. **Required Education & Certifications:** - Bachelor’s degree in mathematics, statistics, computer science, or a related STEM discipline. - Optional: Master’s or PhD in a quantitative field. - No mandatory certifications required; experience with industry tools and ML lifecycle is essential.

London, United kingdom

Hybrid

28-01-2026

Company Name

Women in Data®

Job Title

Machine Learning Engineer

Job Description

Job Title: Machine Learning Engineer Role Summary Responsible for designing, implementing, and maintaining MLOps and Agentic Ops frameworks to move offline machine learning models into scalable production environments. Drives best‑practice adoption, collaborates across data and engineering teams, and ensures seamless model integration with existing systems. Expectations Deliver robust, production‑grade ML infrastructure that meets quality, scalability, and security standards. Mentor peers in MLOps practices, share knowledge through internal and external communities, and proactively evaluate emerging technologies for capability enhancement. Key Responsibilities - Design and develop MLOps and Agentic Ops pipelines for model lifecycle management. - Convert data‑science prototypes into fully functional ML services. - Define and enforce best practices for model training, deployment, monitoring, and rollback. - Build and maintain scalable, secure microservices on Azure Databricks, Azure ML, and related ecosystems. - Contribute production‑ready code, conduct code reviews, and ensure CI/CD compliance. - Stay current with Azure, Databricks, MLflow, PySpark, Git, and MLOps trends; recommend improvements. - Communicate complex technical concepts to non‑technical stakeholders and facilitate cross‑functional collaboration. Required Skills - Proven experience building and operating end‑to‑end ML pipelines. - Strong command of Azure Databricks, Azure ML, MLflow, Git, Python, and PySpark. - Expertise in microservices architecture, DevOps, and MLOps/Agentic Ops practices. - Solid software development fundamentals, including version control, automated testing, and CI/CD. - Excellent communication and collaboration abilities. - Ability to explain technical solutions to business stakeholders. Required Education & Certifications - Bachelor’s degree (or higher) in Computer Science, Engineering, Data Science, or a related field. - Eligibility and authorization to work in the United Kingdom.

Redhill, United kingdom

Hybrid

11-02-2026